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CPIQ - A Privacy Impact Quantification for Digital Medical Consent

Appenzeller, Arno ORCID iD icon; Kadow, Thomas; Krempel, Erik; Beyer, Jürgen


Increasing digitization in healthcare promises easier exchange and more efficient use of medical information for patients, institutions and research. The number of sharing options for medical data increases, e.g., through personal health records, as well as the volume of data. To use this data in medical research patients’ consent is important. As more and more data access is regulated by consent forms and their complexity also increases. For the patient, it becomes less comprehensible which information could be gained from his or her disclosed data. This becomes more important when pressumably anonymized data has the risk of potential re-identification of an individual. In this paper we introduce a consent-privacy-impact-quantification (CPIQ) as a risk model of consent forms for the release of personal medical data for use within research projects. CPIQ evaluates how reasonable a consent decision is for the patient. It takes relevant factors such as the patient’s preferences into account, the circumstances and benefits of the research project, and the potential risk to the patient. The model can be parameterized so that different aspects such as the benefit of the research project, the risk of a data leak or the risk of a patient’s confidential data becoming known can be represented. ... mehr

DOI: 10.1145/3453892.3461653
Zitationen: 2
Zitationen: 2
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 06.2021
Sprache Englisch
Identifikator ISBN: 978-1-4503-8792-7
KITopen-ID: 1000134524
Erschienen in PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June, 2021- 2 July, 2021
Veranstaltung 14th PErvasive Technologies Related to Assistive Environments Conference (PETRA 2021), Korfu, Griechenland, 29.06.2021 – 02.07.2021
Verlag Association for Computing Machinery (ACM)
Seiten 534–543
Vorab online veröffentlicht am 29.06.2021
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